Many elderly tend to be prone to losing their balance and falling. Such falls result in breaks, fractures, and even mortalities. According to the Centers for Disease Control, the annualized rate of fall/collision injury episodes for adults, aged 65 years and over who were not institutionalized in 2001-2003, was 51 episodes per 1,000 people. Annually, one in three Americans over the age of 65 experiences a fall/collision and many of these falls/collisions are recurrent. Further, nearly 60% of older adults who experienced injuries due to falling visited an emergency room for treatment or advice.
EEG, NIRS, and other neural-imaging techniques are becoming more useful in being able to detect certain states of mind prior to the subject actually knowing how he or she feels. It is known that brain signals can be used to indicate a person's current activity state and to predict a change in the person's activity state. These techniques can be used for event detection (i.e., the early detection of falls, startling reflexes).
Prior art systems have discussed deploying personal safety devices based on event detection. For example, a number of prior art systems discuss approaches to deploying airbag systems for protecting a wearer during a fall or other accident. However the majority of prior art systems are aesthetically unpleasing which is directly correlated with reduced compliance in wearing the personal safety devices.
Additionally, prior art systems face problems associated with the timing and sensitivity of detecting falls. For example, the prior art systems may not be able to detect a fall/startling movement with confidence until there is not enough time to deploy a safety device to prevent injury during the fall/startling movement. This may be in part due to the fact that the prior art systems typically depend entirely on accelerometers or gyroscopes to detect and respond to movement. Signals obtained from the accelerometers or gyroscopes which indicate a fall/startling movement may be available only after the fall is already initiated and in progress. Accordingly, there may not be enough time after a fall is detected from signals obtained from the accelerometers or gyroscopes to deploy the safety device.
Prior art systems may also suffer from a high degree of sensitivity leading to a high number of false detections of falling events (i.e., false positives). This is due in part to prior art systems relying on information solely from gyroscopes and accelerometers. In signals acquired from gyroscopes and accelerometers intentional movements such as laughing, dancing, jumping, turns, and the like may have similar motion profiles as the motion profiles associated with unintended movement such as falls and startling effects. Accordingly, in prior art systems which solely utilized gyroscopes and accelerometers it would be impossible to distinguish between intentional and unintentional movements, leading to a high number of false positives.
Accordingly, it would be beneficial to provide a system and a method for detecting body signals indicative of an imminent fall and/or startling movement and activating a safety device to mitigate damage or injury resulting from the fall and/or startling movement. There is a need for faster and more accurate systems for detecting unintentional movements such as falls and/or startling movement. Furthermore, due to vast variations in the causes, pathologies and scenarios of falling and/or startling movements, such a system should be capable of adapting its performance to the specific and individual user.